openl Get Test Results

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses key behavioral traits: pagination granularity (tables vs. test cases), parameter mutual exclusions (page vs. offset, unpaged vs. pagination), and filtering options. No annotations contradict; openWorldHint is benign. However, does not mention rate limits or side effects beyond the read operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise at about 5 sentences. Front-loaded with main purpose and uses 'IMPORTANT' to highlight key behavior. No unnecessary information, though could be slightly tighter.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers prerequisite and pagination behavior well, but lacks detail on the output structure (no output schema). Description mentions 'testCases array grouped by table' but does not fully describe return fields. Sufficient for basic usage but incomplete for advanced scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% description coverage, but description adds critical context that pagination parameters affect tables, not test cases. Reinforces mutual exclusivity and provides conceptual understanding beyond schema definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool gets full test execution results with pagination support, and specifies that results are grouped by table. Differentiates from sibling tools like openl_get_test_results_by_table and openl_get_test_results_summary by emphasizing 'full' and 'grouped by table'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states prerequisite (use openl_start_project_tests() first) and explains pagination applies to test tables, not individual test cases. Provides context on when to use filtering and pagination, but lacks explicit when-not-to-use scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.